Transfer Learning
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Deep Domain Confusion: Maximizing for Domain Invariance
Tzeng E , Hoffman J , Zhang N , et al. Deep Domain Confusion: Maximizing for Domain Invariance[J]. Computer Science, 2014.主要使用两个损失函数：1） 对于source domain上（默认有label）数据 （以及target domain上有label的数据）的分类误差进...原创 2019-07-07 22:08:54 · 1071 阅读 · 0 评论 -
Beyond sharing weights for deep domain adaptation (PAMI 2018) ---Transfer Learning
Rozantsev, Artem, Mathieu Salzmann, and Pascal Fua. “Beyond sharing weights for deep domain adaptation.” IEEE transactions on pattern analysis and machine intelligence 41.4 (2018): 801-814. (Domain Ad...原创 2019-07-09 14:39:54 · 1112 阅读 · 2 评论 -
Domain Separation Networks (NIPS 2016)
Bousmalis, K., Trigeorgis, G., Silberman, N., Krishnan, D., & Erhan, D. (2016). Domain separation networks. NIPS 2016.网络结构：输入图像为xxx。对于target domain 有两个特征提取网络： Ec(x),Eps(xs)E_c(x),E_p^s(x^s)Ec...原创 2019-07-12 22:36:22 · 1240 阅读 · 0 评论 -
Deep coral: Correlation alignment for deep domain adaptation. ECCV 2016. Domain Adaptation
** Sun, Baochen, and Kate Saenko. “Deep coral: Correlation alignment for deep domain adaptation.” ECCV. Springer, Cham, 2016. **结构如图：两个损失函数：其中LCLASS\mathcal{L}_{CLASS}LCLASS为分类损失，LCORAL\mathcal{...原创 2019-07-14 19:15:58 · 1173 阅读 · 0 评论 -
Unsupervised domain adaptation with residual transfer networks(NIPS 2016)
Long, Mingsheng, et al. “Unsupervised domain adaptation with residual transfer networks.” Advances in Neural Information Processing Systems. 2016.问题：domain adaptation用于分类问题。其中source domain具有label，ta...原创 2019-07-15 11:09:32 · 1346 阅读 · 0 评论 -
笔记： Gradient Reversal Layer (unsupervised domain adaptation by backpropagation. ICML 2015)
paper: Ganin, Yaroslav, and Victor Lempitsky. “Unsupervised domain adaptation by backpropagation.” ICML 37. JMLR. org, 2015.论文用**domain adaptation **算法解决目标域无标签的分类问题。文章假设source domain有数据xxx,和label yyy...原创 2019-07-06 22:57:30 · 7153 阅读 · 0 评论 -
Unsupervised pixel-level domain adaptation with generative adversarial networks (DA+ 图像转换)
**Bousmalis, Konstantinos, et al. “Unsupervised pixel-level domain adaptation with generative adversarial networks.” CVPR2017. **问题背景：将原域的图像转换到目标域。已知源域的图像类别标签，对于目标域的图像标签未知。损失函数1. 域对抗损失：2. 分类损失...原创 2019-08-05 16:27:14 · 883 阅读 · 0 评论 -
Progressive Feature Alignment for Unsupervised Domain Adaptation-CVPR2019.md
Progressive Feature Alignment for Unsupervised Domain Adaptation (CVPR2019)提出了一个逐步特征对齐网络 Progressive Feature Alignment Network (PFAN)去解决原域有标签、目标域无标签的无监督domain adaptation分类问题：Easy-to-Hard 迁移策略 (EHT...原创 2019-09-09 16:01:45 · 1972 阅读 · 0 评论 -
Transferrable Prototypical Networks for Unsupervised Domain Adaptation (CVPR 2019)
Transferrable Prototypical Networks for Unsupervised Domain Adaptation论文: Yingwei Pan, Ting Yao, Yehao Li, Yu Wang, Chong-Wah Ngo, Tao Mei. Transferrable Prototypical Networks for Unsupervised Domain...原创 2019-09-11 19:58:53 · 1503 阅读 · 1 评论